Communication has traditionally been carried out over very reliable networks, such as phone lines and fiber optics. With the exploding popularity of newer mediums, such as the Internet and wireless networks (e.g., satellite, cellular, etc.), an increasingly larger percentage of communication is being conducted over more non-traditional networks. The newer networks offer numerous advantages over their traditional counterparts. Unfortunately, reliability is not necessarily one of them. In comparison to the older communication channels, some of the newer forms of communications channels are prone to errors.
Delivering multimedia content over error-prone networks, such as the Internet and wireless networks, presents difficult challenges in terms of both efficiency and reliability. Digital images and video pose a particular problem because they often represent the largest percentage or most significant portion of the multimedia content.
Traditionally, images being transmitted over error-prone channels were first compressed using variable length coding (VLC). For example, JPEG and MPEG both use variable length coding. Unfortunately, one characteristic of variable length coding is that it is very sensitive to errors. A single bit error usually results in loss of synchronization and contents between the previous and next synchronization codewords are usually discarded. Also, once an error is introduced into the bitstream at the receiver, it is difficult to recover the entire image. In error-prone channels, errors are likely to occur and thus variable length coding is not a suitable coding technique.
One prior art solution to coding images in a manner that is less sensitive to errors is to use vector quantization (VQ). Vector quantization is a fixed length coding scheme that, unlike the popular VLC scheme, limits bit errors within a codeword such that no error propagation takes place. Thus, VQ is a more preferred coding technique than VLC.
A separate problem concerning communication over error-prone channels is the ability to ensure delivery of at least the most important parts of a transmission. That is, different parts of any given bitstream are more important than other parts. In the video context, for example, lower frequency components are considered to be more important than higher frequency components. Important components deserve higher protection over an error-prone channel to ensure proper delivery.
To address the coding efficiency, another prior art coding scheme uses a fixed-length coding. The coding scheme is based on vector transformation (VT) and vector quantization (VQ), and is sometimes short-handedly referred to as “VTQ”. VTQ outperforms scalar transform and scalar quantization in coding efficiency. The fundamental reason is that the vector transform reduces inter vector correlation while preserving intra vector correlation in a better manner than scalar transform. With this property, the efficiency of vector quantization is significantly improved.
The VTQ coding scheme is described in more detail in Weiping Li and Ya-Qin Zhang, “Vector-Based Signal Processing and Quantization for Image and Video Compression”, Proceedings of the IEEE, Vol. 83, No. 2, February 1995, and in Weiping Li and Ya-Qin Zhang, “New insights and results on transform domain VQ of images,” in Proc. IEEE Conf. Acoustics, Speech, and Signal Processing, Minneapolis, Minn., April. 1993, pp. V607-V612.
The coding scheme described below is an improvement of the Li and Zhang coding scheme.